Arvind Hulgeri

Keyword searching and browsing in databases using BANKS

With the growth of the Web, there has been a rapid increase in the number of users who need to access online databases without having a detailed knowledge of the schema or of query languages; even relatively simple query languages designed for non-experts are too complicated for them. We describe BANKS, a system which enables keyword-based search on relational databases, together with data and schema browsing. BANKS enables users to extract information in a simple manner without any knowledge of the schema or any need for writing complex queries. A user can get information by typing a few keywords, following hyperlinks, and interacting with controls on the displayed results. BANKS models tuples as nodes in a graph, connected by links induced by foreign key and other relationships. Answers to a query are modeled as rooted trees connecting tuples that match individual keywords in the query. Answers are ranked using a notion of proximity coupled with a notion of prestige of nodes based on inlinks, similar to techniques developed for Web search. We present an efficient heuristic algorithm for finding and ranking query results.

BANKS: browsing and keyword searching in relational databases

Publisher Summary Browsing ANd Keyword Searching (BANKS) enables almost effortless Web publishing of relational and eXtensible Markup Language (XML) data that would otherwise remain (at least partially) invisible to the Web. Relational databases store large amounts of data that are queried using structured query languages. A user needs to know the underlying schema and the query language in order to make meaningful ad hoc queries on the data. This is a substantial barrier for casual users, such as users of Web-based information systems. HTML forms can be provided for predefined queries. A university Website may provide a form interface to search for faculty and students. Searching for departments would require yet another form, as would search for courses offered. However, creating an interface for each such task is laborious, and is also confusing to users since they must first expend effort finding which form to use. Furthermore, they are not suitable for ad hoc querying or exploratory browsing. Search engines on the Web have popularized an alternative unstructured querying and browsing paradigm that is simple and user-friendly. Users type in keywords and then follow hyperlinks to navigate from one document to the other. No knowledge of schema is needed. Keyword search can provide a very simple and easy-to-use mechanism for casual users to get information from databases.

Parametric query optimization for linear and piecewise linear cost functions

The cost of a query plan depends on many parameters, such as predicate selectivities and available memory, whose values may not be known at optimization time. Parametric query optimization (PQO) optimizes a query into a number of candidate plans, each optimal for some region of the parameter space. We first propose a solution for the PQO problem for the case when the cost functions are linear in the given parameters. This solution is minimally intrusive in the sense that an existing query optimizer can be used with minor modifications: the solution invokes the conventional query optimizer multiple times, with different parameter values. We then propose a solution for the PQO problem for the case when the cost functions are piecewise-linear in the given parameters. The solution is based on modification of an existing query optimizer. This solution is quite general, since arbitrary cost functions can be approximated to piecewise linear form. Both the solutions work for an arbitrary number of parameters.

AniPQO: almost non-intrusive parametric query optimization for nonlinear cost functions

The cost of a query plan depends on many parameters, such as predicate selectivities and available memory, whose values may not be known at optimization time. Parametric query optimization (PQO) optimizes a query into a number of candidate plans, each optimal for some region of the parameter space. We propose a heuristic solution for the PQO problem for the case when the cost functions may be nonlinear in the given parameters. This solution is minimally intrusive in the sense that an existing query optimizer can be used with minor modifications. We have implemented the heuristic and the results of the tests on the TPCD benchmark indicate that the heuristic is very effective. The minimal intrusiveness, generality in terms of cost functions and number of parameters and good performance (up to 4 parameters) indicate that our solution is of significant practical importance.

User interaction in the BANKS system: a demonstration

The BANKS system supports keyword search on databases storing structured/semi-structured data. Answers to keyword queries are ranked. As in Information Retrieval (IR) systems, the top answers may not be exactly what a user is looking for. Further interaction with the system is required to narrow in on desired answers. We describe some of the new features that we have added to the BANKS system to improve user interaction. These include an extended query model, richer support for user feedback and better display of answers.

Chapter 107 – BANKS: Browsing and Keyword Searching in Relational Databases*

Publisher Summary Browsing ANd Keyword Searching (BANKS) enables almost effortless Web publishing of relational and eXtensible Markup Language (XML) data that would otherwise remain (at least partially) invisible to the Web. Relational databases store large amounts of data that are queried using structured query languages. A user needs to know the underlying schema and the query language in order to make meaningful ad hoc queries on the data. This is a substantial barrier for casual users, such as users of Web-based information systems. HTML forms can be provided for predefined queries. A university Website may provide a form interface to search for faculty and students. Searching for departments would require yet another form, as would search for courses offered. However, creating an interface for each such task is laborious, and is also confusing to users since they must first expend effort finding which form to use. Furthermore, they are not suitable for ad hoc querying or exploratory browsing. Search engines on the Web have popularized an alternative unstructured querying and browsing paradigm that is simple and user-friendly. Users type in keywords and then follow hyperlinks to navigate from one document to the other. No knowledge of schema is needed. Keyword search can provide a very simple and easy-to-use mechanism for casual users to get information from databases.

BANKS: Browsing and Keyword Searching in Relational Databases**Partly supported by an IBM Faculty Fellowship grant and an Infosys Ph.D. Fellowship.

Publisher Summary Browsing ANd Keyword Searching (BANKS) enables almost effortless Web publishing of relational and eXtensible Markup Language (XML) data that would otherwise remain (at least partially) invisible to the Web. Relational databases store large amounts of data that are queried using structured query languages. A user needs to know the underlying schema and the query language in order to make meaningful ad hoc queries on the data. This is a substantial barrier for casual users, such as users of Web-based information systems. HTML forms can be provided for predefined queries. A university Website may provide a form interface to search for faculty and students. Searching for departments would require yet another form, as would search for courses offered. However, creating an interface for each such task is laborious, and is also confusing to users since they must first expend effort finding which form to use. Furthermore, they are not suitable for ad hoc querying or exploratory browsing. Search engines on the Web have popularized an alternative unstructured querying and browsing paradigm that is simple and user-friendly. Users type in keywords and then follow hyperlinks to navigate from one document to the other. No knowledge of schema is needed. Keyword search can provide a very simple and easy-to-use mechanism for casual users to get information from databases.